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Introduction to Natural Language Processing (Adaptive Computation and Machine Learning series),Used
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A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques.This textbook provides a technical perspective on natural language processingmethods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary datadriven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to wordbased textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapterlength treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. Endofchapter exercises include both paperandpencil analysis and software implementation.The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduatelevel courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and collegelevel mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
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